FSS-based Evaluation on Monsoon Precipitation Forecasts in South China from Regional Models with Different Resolution

Abstract

: This study evaluated the forecast skill of CMA-GD 3 km and CMA-GD 1 km with hourly Rapid Update Cycle (RUC) for five monsoon precipitation events in South China from 2018 to 2020, using the fraction skill score (FSS) of the neighborhood spatial verification method. The results revealed that, among the 24-lead-hour forecasts in CMA-GD 3 km, the FSS for the 0.1 mm precipitation threshold increased linearly with the lead time from 3 to 1 hour, while there was no significant improvement in other lead times. For the 5 mm precipitation threshold, the forecast skill was highest for the latest 1-hour lead time, while the FSS showed slight variation between lead times of 24 hours and 8 hours. The FSS for 10 mm and 20 mm precipitation thresholds were similar to that of 5 mm, with the difference that the best score occurred at the 2-hour lead time. Among the 6-lead-hour forecasts in CMA-GD 1 km, the forecasts of the latest 1-hour lead time were the best choices for four precipitation thresholds. When comparing CMA-GD 3 km and CMA-GD 1 km, it was found that CMA-GD 3 km had better skill for forecasts of 0.1 mm and 5 mm precipitation at 2-hour and 1-hour lead times, while CMA-GD 1 km had better skill for all other forecasts, including the forecast of 20 mm precipitation nearly all lead hours (including 3-to 6-hour, and 1-hour lead times). The results suggest that the increased resolution of the model may be beneficial for precipitation forecasts in South China, especially for short-duration heavy precipitation over a longer lead hours. However, the limited sample size of this study calls for further evaluation using more cases to validate the results′ generality.